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So I have this new programming paradigm.......

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This commit is contained in:
Joseph Redmon
2016-09-24 23:12:54 -07:00
parent c899cc19f4
commit 481b57a96a
49 changed files with 629 additions and 914 deletions
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121
src/detector.c
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@ -1,16 +1,16 @@
#include "network.h"
#include "detection_layer.h"
#include "region_layer.h"
#include "cost_layer.h"
#include "utils.h"
#include "parser.h"
#include "box.h"
#include "demo.h"
#ifdef OPENCV
#include "opencv2/highgui/highgui_c.h"
#endif
static char *voc_names[] = {"aeroplane", "bicycle", "bird", "boat", "bottle", "bus", "car", "cat", "chair", "cow", "diningtable", "dog", "horse", "motorbike", "person", "pottedplant", "sheep", "sofa", "train", "tvmonitor"};
static image voc_labels[20];
void train_detector(char *cfgfile, char *weightfile)
{
@ -49,13 +49,14 @@ void train_detector(char *cfgfile, char *weightfile)
args.num_boxes = l.max_boxes;
args.d = &buffer;
args.type = DETECTION_DATA;
args.threads = 4;
args.angle = net.angle;
args.exposure = net.exposure;
args.saturation = net.saturation;
args.hue = net.hue;
pthread_t load_thread = load_data_in_thread(args);
pthread_t load_thread = load_data(args);
clock_t time;
//while(i*imgs < N*120){
while(get_current_batch(net) < net.max_batches){
@ -63,7 +64,7 @@ void train_detector(char *cfgfile, char *weightfile)
time=clock();
pthread_join(load_thread, 0);
train = buffer;
load_thread = load_data_in_thread(args);
load_thread = load_data(args);
/*
int k;
@ -102,44 +103,6 @@ void train_detector(char *cfgfile, char *weightfile)
save_weights(net, buff);
}
static void convert_detections(float *predictions, int classes, int num, int square, int side, int w, int h, float thresh, float **probs, box *boxes, int only_objectness)
{
int i,j,n;
//int per_cell = 5*num+classes;
for (i = 0; i < side*side; ++i){
int row = i / side;
int col = i % side;
for(n = 0; n < num; ++n){
int index = i*num + n;
int p_index = index * (classes + 5) + 4;
float scale = predictions[p_index];
int box_index = index * (classes + 5);
boxes[index].x = (predictions[box_index + 0] + col + .5) / side * w;
boxes[index].y = (predictions[box_index + 1] + row + .5) / side * h;
if(0){
boxes[index].x = (logistic_activate(predictions[box_index + 0]) + col) / side * w;
boxes[index].y = (logistic_activate(predictions[box_index + 1]) + row) / side * h;
}
boxes[index].w = pow(logistic_activate(predictions[box_index + 2]), (square?2:1)) * w;
boxes[index].h = pow(logistic_activate(predictions[box_index + 3]), (square?2:1)) * h;
if(1){
boxes[index].x = ((col + .5)/side + predictions[box_index + 0] * .5) * w;
boxes[index].y = ((row + .5)/side + predictions[box_index + 1] * .5) * h;
boxes[index].w = (exp(predictions[box_index + 2]) * .5) * w;
boxes[index].h = (exp(predictions[box_index + 3]) * .5) * h;
}
for(j = 0; j < classes; ++j){
int class_index = index * (classes + 5) + 5;
float prob = scale*predictions[class_index+j];
probs[index][j] = (prob > thresh) ? prob : 0;
}
if(only_objectness){
probs[index][0] = scale;
}
}
}
}
void print_detector_detections(FILE **fps, char *id, box *boxes, float **probs, int total, int classes, int w, int h)
{
int i, j;
@ -179,7 +142,6 @@ void validate_detector(char *cfgfile, char *weightfile)
layer l = net.layers[net.n-1];
int classes = l.classes;
int side = l.w;
int j;
FILE **fps = calloc(classes, sizeof(FILE *));
@ -188,9 +150,9 @@ void validate_detector(char *cfgfile, char *weightfile)
snprintf(buff, 1024, "%s%s.txt", base, voc_names[j]);
fps[j] = fopen(buff, "w");
}
box *boxes = calloc(side*side*l.n, sizeof(box));
float **probs = calloc(side*side*l.n, sizeof(float *));
for(j = 0; j < side*side*l.n; ++j) probs[j] = calloc(classes, sizeof(float *));
box *boxes = calloc(l.w*l.h*l.n, sizeof(box));
float **probs = calloc(l.w*l.h*l.n, sizeof(float *));
for(j = 0; j < l.w*l.h*l.n; ++j) probs[j] = calloc(classes, sizeof(float *));
int m = plist->size;
int i=0;
@ -235,12 +197,12 @@ void validate_detector(char *cfgfile, char *weightfile)
char *path = paths[i+t-nthreads];
char *id = basecfg(path);
float *X = val_resized[t].data;
float *predictions = network_predict(net, X);
network_predict(net, X);
int w = val[t].w;
int h = val[t].h;
convert_detections(predictions, classes, l.n, 0, side, w, h, thresh, probs, boxes, 0);
if (nms) do_nms_sort(boxes, probs, side*side*l.n, classes, nms);
print_detector_detections(fps, id, boxes, probs, side*side*l.n, classes, w, h);
get_region_boxes(l, w, h, thresh, probs, boxes, 0);
if (nms) do_nms_sort(boxes, probs, l.w*l.h*l.n, classes, nms);
print_detector_detections(fps, id, boxes, probs, l.w*l.h*l.n, classes, w, h);
free(id);
free_image(val[t]);
free_image(val_resized[t]);
@ -268,8 +230,6 @@ void validate_detector_recall(char *cfgfile, char *weightfile)
layer l = net.layers[net.n-1];
int classes = l.classes;
int square = l.sqrt;
int side = l.side;
int j, k;
FILE **fps = calloc(classes, sizeof(FILE *));
@ -278,9 +238,9 @@ void validate_detector_recall(char *cfgfile, char *weightfile)
snprintf(buff, 1024, "%s%s.txt", base, voc_names[j]);
fps[j] = fopen(buff, "w");
}
box *boxes = calloc(side*side*l.n, sizeof(box));
float **probs = calloc(side*side*l.n, sizeof(float *));
for(j = 0; j < side*side*l.n; ++j) probs[j] = calloc(classes, sizeof(float *));
box *boxes = calloc(l.w*l.h*l.n, sizeof(box));
float **probs = calloc(l.w*l.h*l.n, sizeof(float *));
for(j = 0; j < l.w*l.h*l.n; ++j) probs[j] = calloc(classes, sizeof(float *));
int m = plist->size;
int i=0;
@ -299,18 +259,19 @@ void validate_detector_recall(char *cfgfile, char *weightfile)
image orig = load_image_color(path, 0, 0);
image sized = resize_image(orig, net.w, net.h);
char *id = basecfg(path);
float *predictions = network_predict(net, sized.data);
convert_detections(predictions, classes, l.n, square, l.w, 1, 1, thresh, probs, boxes, 1);
if (nms) do_nms(boxes, probs, side*side*l.n, 1, nms);
network_predict(net, sized.data);
get_region_boxes(l, 1, 1, thresh, probs, boxes, 1);
if (nms) do_nms(boxes, probs, l.w*l.h*l.n, 1, nms);
char *labelpath = find_replace(path, "images", "labels");
labelpath = find_replace(labelpath, "JPEGImages", "labels");
labelpath = find_replace(labelpath, ".jpg", ".txt");
labelpath = find_replace(labelpath, ".JPEG", ".txt");
char labelpath[4096];
find_replace(path, "images", "labels", labelpath);
find_replace(labelpath, "JPEGImages", "labels", labelpath);
find_replace(labelpath, ".jpg", ".txt", labelpath);
find_replace(labelpath, ".JPEG", ".txt", labelpath);
int num_labels = 0;
box_label *truth = read_boxes(labelpath, &num_labels);
for(k = 0; k < side*side*l.n; ++k){
for(k = 0; k < l.w*l.h*l.n; ++k){
if(probs[k][0] > thresh){
++proposals;
}
@ -319,7 +280,7 @@ void validate_detector_recall(char *cfgfile, char *weightfile)
++total;
box t = {truth[j].x, truth[j].y, truth[j].w, truth[j].h};
float best_iou = 0;
for(k = 0; k < side*side*l.n; ++k){
for(k = 0; k < l.w*l.h*l.n; ++k){
float iou = box_iou(boxes[k], t);
if(probs[k][0] > thresh && iou > best_iou){
best_iou = iou;
@ -340,13 +301,12 @@ void validate_detector_recall(char *cfgfile, char *weightfile)
void test_detector(char *cfgfile, char *weightfile, char *filename, float thresh)
{
image *alphabet = load_alphabet();
network net = parse_network_cfg(cfgfile);
if(weightfile){
load_weights(&net, weightfile);
}
detection_layer l = net.layers[net.n-1];
l.side = l.w;
layer l = net.layers[net.n-1];
set_batch_network(&net, 1);
srand(2222222);
clock_t time;
@ -354,9 +314,9 @@ void test_detector(char *cfgfile, char *weightfile, char *filename, float thresh
char *input = buff;
int j;
float nms=.4;
box *boxes = calloc(l.side*l.side*l.n, sizeof(box));
float **probs = calloc(l.side*l.side*l.n, sizeof(float *));
for(j = 0; j < l.side*l.side*l.n; ++j) probs[j] = calloc(l.classes, sizeof(float *));
box *boxes = calloc(l.w*l.h*l.n, sizeof(box));
float **probs = calloc(l.w*l.h*l.n, sizeof(float *));
for(j = 0; j < l.w*l.h*l.n; ++j) probs[j] = calloc(l.classes, sizeof(float *));
while(1){
if(filename){
strncpy(input, filename, 256);
@ -371,12 +331,12 @@ void test_detector(char *cfgfile, char *weightfile, char *filename, float thresh
image sized = resize_image(im, net.w, net.h);
float *X = sized.data;
time=clock();
float *predictions = network_predict(net, X);
network_predict(net, X);
printf("%s: Predicted in %f seconds.\n", input, sec(clock()-time));
convert_detections(predictions, l.classes, l.n, 0, l.w, 1, 1, thresh, probs, boxes, 0);
if (nms) do_nms_sort(boxes, probs, l.side*l.side*l.n, l.classes, nms);
//draw_detections(im, l.side*l.side*l.n, thresh, boxes, probs, voc_names, voc_labels, 20);
draw_detections(im, l.side*l.side*l.n, thresh, boxes, probs, voc_names, voc_labels, 20);
get_region_boxes(l, 1, 1, thresh, probs, boxes, 0);
if (nms) do_nms_sort(boxes, probs, l.w*l.h*l.n, l.classes, nms);
//draw_detections(im, l.w*l.h*l.n, thresh, boxes, probs, voc_names, voc_labels, 20);
draw_detections(im, l.w*l.h*l.n, thresh, boxes, probs, voc_names, alphabet, 20);
save_image(im, "predictions");
show_image(im, "predictions");
@ -392,14 +352,10 @@ void test_detector(char *cfgfile, char *weightfile, char *filename, float thresh
void run_detector(int argc, char **argv)
{
int i;
for(i = 0; i < 20; ++i){
char buff[256];
sprintf(buff, "data/labels/%s.png", voc_names[i]);
voc_labels[i] = load_image_color(buff, 0, 0);
}
char *prefix = find_char_arg(argc, argv, "-prefix", 0);
float thresh = find_float_arg(argc, argv, "-thresh", .2);
int cam_index = find_int_arg(argc, argv, "-c", 0);
int frame_skip = find_int_arg(argc, argv, "-s", 0);
if(argc < 4){
fprintf(stderr, "usage: %s %s [train/test/valid] [cfg] [weights (optional)]\n", argv[0], argv[1]);
return;
@ -412,4 +368,5 @@ void run_detector(int argc, char **argv)
else if(0==strcmp(argv[2], "train")) train_detector(cfg, weights);
else if(0==strcmp(argv[2], "valid")) validate_detector(cfg, weights);
else if(0==strcmp(argv[2], "recall")) validate_detector_recall(cfg, weights);
else if(0==strcmp(argv[2], "demo")) demo(cfg, weights, thresh, cam_index, filename, voc_names, 20, frame_skip, prefix);
}